Find out what's driving your demand and take control
One of the world's largest hotel companies found reducing forecasting errors could help them save millions in labor forecasting and pricing insight. Here's how they did it, and the simple process you can follow too.
Forecasting for hotels and accommodation products has never been easy. And 2021 is especially challenging, because both 2020 and pre-pandemic historical data won't help without external data.
Not sure where to start? Businesses must rely are smart data and machine learning to achieve greater forecasting accuracy. This report will take you through everything you need to know about using smart data to reduce forecasting errors:
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Demand Forecasting: Incorporating events into models for smarter forecasting.
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Labor optimization: Ensuring the right number of drivers and store staff to meet demand.
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PredictHQ has supplemented incomplete data sets, including unticketed events and cancelled events, to power pricing strategies and operational decisions.
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Demand forecasting: Incorporating events into their Antuit-built models to better understand demand across 9600 stores.
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Amazon Alexa's "Events Near Me" feature uses PredictHQ data to inform users about local events.
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Demand forecasting: Getting drivers in the right place ahead of time to improve pick-up times.
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Event visibility: Available in Zartico’s platform enabling deeper insight and smarter decisions.
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Pricing: A key source of intelligence for the OTA Insights platform, enabling smarter pricing.
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Labor optimization: Enriching the Legion Technologies platform, used by retailers to reduce labor inefficiencies.
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